Proceedings Paper

One key advantage of the model-based approach for automatic target recognition (ATR) is the wide range of targets and acquisition scenarios that can be accommodated without algorithm re-training. This accrues from the use of predictive models which can be adjusted to hypothesized scenarios on-line. Approaches which rely on measured signature exemplars as the source of reference data for signature matching are constrained to those scenarios represented in the reference data base. The moving and stationary target recognition (MSTAR) program will advance the state-of-the-art in model-based ATR by developing, evaluating, and testing algorithm performance against a set of extended operating conditions (EOCs) designed to reflect real-world battlefield scenarios. In addition to full 360 deg target aspect coverage over a range of depression angles, the EOCs include variations in squint angle, target articulation and configurations, obscuration due to occlusion and/or layover, and intra-class target variability. These conditions can have a profound impact on the nature of the target signature, necessitating the development of explicit prediction and reasoning algorithms to provide robust target recognition. This paper provides a tutorial description of the impact of the MSTAR EOCs on SAR target signatures. A brief background discussion of the SAR imaging process is presented first. This is followed by a description of the impact of each EOC category on the target signature along with synthetic imagery examples to illustrate this impact.